Methods and apparatus for assessing activity of an organ and uses thereof

ABSTRACT

Methods and apparatus are provided for imaging activity of an organ of a subject for diagnosis and prognosis of pathology or injury to the organ, where unaffected portions of the organ are used as a reference for assessing activity of afflicted areas of the organ.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional PatentApplication No. 61/498,243, filed on Jun. 17, 2011, the content of whichis incorporated herein by reference in its entirety.

FIELD

This invention relates to methods and apparatus for imaging activity ofan organ of a subject for diagnosis and prognosis of pathology or injuryto the organ, where unaffected portions of the organ are used as areference for assessing activity of afflicted areas of the organ.

BACKGROUND

Throughout this application various publications are referred to inparenthesis. Full citations for these references may be found at the endof the specification immediately preceding the claims. The disclosuresof these publications are hereby incorporated by reference in theirentireties into the subject application to more fully describe the artto which the subject application pertains.

Nuclear medicine involves the noninvasive quantification ofphysiological processes. In the case of positron emission tomography(PET), fluorine-18 deoxyglucose (FDG) has proven to be a remarkably goodway of tracing the level of physiological glucose metabolism in livingcells. Uptake of fluorine-18 deoxyglucose is proportional to the numberof glucose transporter 1 (GLUT1) receptors expressed on the cellsurface. The number of GLUT1 receptors on the surface is regulated bythe cell in accord with its level of internally sensed demand forglucose. Once FDG glucose enters the cell, further metabolism isprevented by the lack of oxygen within the constructor. Thus, one has anideal physiological tracer for glucose uptake, separated from furtherintracellular stages of glucose metabolism. New and improved PETscanners continue to be developed (e.g., Shiga et al., 2009).

Imaging studies have been used between groups of subjects to demonstrateevidence of injuries or pathologies (e.g., Kato et al., 2007; Zhang etal., 2010). Three dimensional images can be represented using voxels. Avoxel is a data point on a regular grid in three dimensional space. Avoxel, i.e., a volumetric pixel, is analogous to a pixel, whichrepresents two dimensional image data. The data point can consist of asingle piece of datum or multiple pieces of data. Voxel-basedmorphometry is an imaging analysis technique that can be used toinvestigate focal differences in, for example, the brain between twogroups of subjects (e.g., Ashburner and Friston, 2000). Voxel-basedmorphometry studies have been carried out by comparing patients withcontrols, for example in studies of dementia (Mummery et al., 2000) andtraumatic brain injury (Garcia-Panach et al., 2011).

The need for control groups can impede the use of imaging for diagnosis.This is especially the case since there are, for example,gender-specific cerebral areas of age-associated changes of FDG uptake(Kim et al., 2009). For example, accurate diagnosis of diffuse axonalinjury is severely limited by requirements for adequate age- andgender-matched control groups. One widely used software program has only4 patients below age 55; and only 37 patients in the 56-75 year agerange as baseline controls. Other databases are even more lacking. Thus,it is impossible to objectively measure brain injury in those groups ofindividuals most prone to brain injury, i.e., infants, children,adolescents, athletes of age 15 to 30 and motor vehicle accidentsurvivors aged 15 to 55. Data in those younger than 15 are very scarce.

The prevent invention address the need for a method of imaging injuriesand pathologies that does not require comparison of a patient to acontrol group of subjects.

SUMMARY

In exemplary embodiments, the present invention makes use of the normalportions of a patient's own organ to calculate baseline physiologicalfunction. Using the patient as its own control creates far more powerfulimaging and measurement statistics as well as greater reliability forthe relevance of the measurements for the patient's own situation. Withuse of the individual as its own control, the available precision ofmeasurement is vastly improved because one is not required to have areference population of the same age or gender, or same manufacture orsame generation of equipment, or precisely the same protocol of imagingin a reference population. Thus, the present invention can provideimproved technical features over the art.

In exemplary embodiments, the invention provides methods for assessingthe activity of an organ in a subject with the aid of a digital computercomprising: a) accessing by one or more computers a quantitativethree-dimensional image of the organ that is represented as voxels,wherein each voxel contains information about the activity of a portionof the organ; b) calculating by the one or more computers a mean of theactivity represented by the voxels, wherein voxels representing valuesat upper and lower extremes are excluded from calculation of the mean;c) calculating by the one or more computers a standard deviation of themean obtained in step b), wherein voxels representing activity above acertain standard deviation of the mean indicate areas of the organhaving increased activity and wherein voxels representing activity belowa certain standard deviation of the mean indicate areas of the organhaving reduced activity; and d) outputting by the one or more computersto an output device a representation of the organ showing areas of theorgan having increased activity and/or reduced activity. In someexemplary embodiments, the method may further comprise outputting by theone or more computers to the output device a representation of the organshowing areas of the organ having neither increased activity and/orreduced activity.

In exemplary embodiments, the invention also provides systems forassessing the activity of an organ in a subject comprising one or moreprocessors, a memory unit, and a computer-readable storage mediumincluding computer-readable code that is read by the one or moreprocessors to perform a method comprising the steps of: a) accessing byone or more computers a quantitative three-dimensional image of theorgan that is represented as voxels, wherein each voxel containsinformation about the activity of a portion of the organ; b) calculatingby the one or more computers a mean of the activity represented by thevoxels, wherein voxels representing values at upper and lower extremesare excluded from calculation of the mean; c) calculating by the one ormore computers a standard deviation of the mean obtained in step b),wherein voxels representing activity above a certain standard deviationof the mean indicate areas of the organ having increased activity andwherein voxels representing activity below a certain standard deviationof the mean indicate areas of the organ having reduced activity; and d)outputting by the one or more computers to an output device arepresentation of the organ showing areas of the organ having increasedactivity and/or reduced activity.

In exemplary embodiments, the invention further provides systems forassessing the activity of an organ in a subject comprising: a) animaging system comprising: i) an imaging device for generating aquantitative three-dimensional image of the organ that is represented asvoxels, wherein each voxel contains information about the activity of aportion of the organ; and ii) a computing device operatively connectedto the imaging device and to a first display device; and b) one or morecomputers operatively connected to the imaging system, comprising one ormore processors, a memory unit, and a computer-readable storage mediumincluding computer-readable code that is read by the one or moreprocessors to perform a method comprising the steps of: i) receiving bythe one or more computers the generated three-dimensional organ image;ii) calculating by the one or more computers a mean of the activityrepresented by the voxels, wherein voxels representing values at upperand lower extremes are excluded from calculation of the mean; iii)calculating by the one or more computers a standard deviation of themean obtained in step ii), wherein voxels representing activity above acertain standard deviation of the mean indicate areas of the organhaving increased activity and wherein voxels representing activity belowa certain standard deviation of the mean indicate areas of the organhaving reduced activity; and iv) generating by the one or more computersa representation of the organ showing areas of the organ havingincreased activity and/or reduced activity.

In exemplary embodiments, the invention still further provides systemsfor assessing the activity of an organ in a subject comprising: a) oneor more computing devices comprising one or more processors, a memoryunit, and a computer-readable storage medium including computer-readablecode that is read by the one or more processors to perform a methodcomprising the steps of: i) obtaining by the one or more computingdevices a quantitative three-dimensional image of the organ that isrepresented as voxels, wherein each voxel contains information about theactivity of a portion of the organ generated by an imaging device; ii)transmitting the generated three-dimensional organ image to one or moreanalysis computing devices; iii) obtaining a representation of the organfrom the one or more analysis computing devices, wherein therepresentation shows areas of the organ having increased activity and/orreduced activity; and iv) displaying the obtained representation on thedisplay device.

BRIEF DESCRIPTION OF THE DRAWINGS

The features and advantages of the disclosure can be more fullyunderstood with reference to the following description of the disclosurewhen taken in conjunction with the accompanying figures, wherein:

FIG. 1 is a flow chart illustrating an exemplary method for identifyingvoxels having inactivity and/or compensatory activity in comparison to abaseline of the normal portions of the entire brain according to anexemplary embodiment of the present disclosure.

FIG. 2 is a schematic representation illustrating a imaging systemoperatively connected to one or more computing devices according to anexemplary embodiment of the present disclosure.

FIG. 3 is a flow chart illustrating an exemplary method for assessingthe activity of an organ in a subject according to an exemplaryembodiment of the present disclosure.

FIGS. 4A-4D are exemplary charts showing results of variouspsychometrics tests performed with a subject over a one year period.

FIG. 5A-5B show comparative quantitative PET images showing significantimprovement in Case Study #1 from May 2011 (A) to February 2012 (B)consistent with improved cognitive scores.

DETAILED DESCRIPTION

In exemplary embodiments, the invention may provide a method forassessing the activity of an organ in a subject with the aid of adigital computer comprising:

a) accessing by one or more computers a quantitative three-dimensionalimage of the organ that is represented as voxels, wherein each voxelcontains information about the activity of a portion of the organ;

b) calculating by the one or more computers a mean of the activityrepresented by the voxels, wherein voxels representing values at upperand lower extremes are excluded from calculation of the mean;

c) calculating by the one or more computers a standard deviation of themean obtained in step b), wherein voxels representing activity above acertain standard deviation of the mean indicate areas of the organhaving increased activity and wherein voxels representing activity belowa certain standard deviation of the mean indicate areas of the organhaving reduced activity; and

d) outputting by the one or more computers to an output device arepresentation of the organ showing areas of the organ having increasedactivity and/or reduced activity.

In exemplary embodiments, the method may comprise outputting by the oneor more computers to the output device a representation of the organshowing areas of the organ having neither increased activity and/orreduced activity.

In exemplary embodiments, the invention may provide a system forassessing the activity of an organ in a subject comprising one or moreprocessors, a memory unit, and a computer-readable storage mediumincluding computer-readable code that is read by the one or moreprocessors to perform a method comprising the steps of:

a) accessing by one or more computers a quantitative three-dimensionalimage of the organ that is represented as voxels, wherein each voxelcontains information about the activity of a portion of the organ;

b) calculating by the one or more computers a mean of the activityrepresented by the voxels, wherein voxels representing values at upperand lower extremes are excluded from calculation of the mean;

c) calculating by the one or more computers a standard deviation of themean obtained in step b), wherein voxels representing activity above acertain standard deviation of the mean indicate areas of the organhaving increased activity and wherein voxels representing activity belowa certain standard deviation of the mean indicate areas of the organhaving reduced activity; and

d) outputting by the one or more computers to an output device arepresentation of the organ showing areas of the organ having increasedactivity and/or reduced activity.

In exemplary embodiments, the system may comprise outputting by the oneor more computers to the output device a representation of the organshowing areas of the organ having neither increased activity and/orreduced activity.

Various values can be selected for use in excluding voxels representingvalues at upper and lower extremes from the calculation of the mean. Asnon-limiting examples, voxels can be excluded from calculation of themean if the voxels represent values at the upper and lower 1%, 5% or 10%of the values.

In exemplary embodiments, other methods of excluding vowels thatrepresent outlier values may be used. As one example, a first mean canbe calculated of the activity represented by all the voxels. Then,voxels representing values at the upper and lower values can beexcluded, either if the values are above or below a certain percentageof all values or if the values are above or below a certain standarddeviation of the first mean. The voxels that are not excluded are thenused to calculate a new mean of normal voxels.

Another method of excluding vowels that represent outlier values is toconstruct a histogram of values represented by all voxels, then fittinga curve to the histogram, and excluding voxels that deviate above orbelow the curve. These procedures can be performed by the one or morecomputers that calculated a mean of the activity represented by thevoxels where voxels representing values at upper and lower extremes areexcluded from calculation of the mean.

Standard deviation (SD) of the mean can be expressed, for example in1SD, 0.1 SD or 0.01 SD units. For example, SD can be calculated in 0.01or 0.1 SD units between 3.0, 3.5, 4.0 or 4.5 SD units below the mean to3.0, 3.5, 4.0 or 4.5 SD units above the mean. As a further example, inone embodiment, standard deviation (SD) is calculated in 0.1 SD unitsbetween 4.0 SD units below the mean to 4.0 SD units above the mean.

In exemplary embodiments, different thresholds can be established forclassifying voxels as representing increased activity or decreasedactivity. For example, a threshold can be set at 1.0 SD, 1.5 SD, 1.65SD, 2.0 SD, 2.5 SD, 3.0, 3.5, 4.0 or 4.5 SD units above or below themean. As a further example, in one embodiment, voxels representingactivity above 1.5 SD units above the mean indicate areas of the organhaving increased activity and voxels representing activity below 1.5 SDunits below the mean indicate areas of the organ having reducedactivity. Other variations can be used consistent with the letter andspirit of the present disclosure.

The organ from which the image is obtained can be, for example, brain,heart, lung, kidney, liver, pancreas, bladder, salivary glands,esophagus, stomach, gallbladder, intestines, colon, rectum, thyroid,parathyroid, adrenal gland, ureter, bladder, urethra, tonsils, adenoids,thymus, spleen, ovary, fallopian tube, uterus, vagina, mammary gland,testes, vas deferens, seminal vesicle, prostate, penis, pharynx, larynx,trachea, bronchi or lung, to name a few.

In exemplary embodiments, voxels from the one side of an organ can becompared with corresponding voxels from an opposite side of the sameorgan. For organs that occur on both sides of the body, such as forexample, brain, lung or kidney, in exemplary embodiments, voxels from anorgan on one side of the body can be compared with corresponding voxelsfrom the corresponding organ on the opposite side of the body.

In exemplary embodiments, the image of the organ can be obtained using,for example, positron emission tomography (PET), functional magneticresonance imaging (fMRI), any type or sequence of magnetic resonanceimaging (MRI) including diffusion tensor magnetic resonance imaging,single photon emission computed tomography (SPECT), magnetic sourceimaging or optical imaging, to name a few. For example, threedimensional imaging of the organ can be obtained using positron emissiontomography (PET) in connection with a computed tomography (CT) X-rayscan, or may be obtained using positron emission tomography (PET) inconnection with any magnetic resonance scan.

Dedicated brain-only solid-state PET scanners are being developed byHitachi. Such units may provide essential physiological information fora much lower patient radiation dose than existing PET CT machines. A PETCT general-purpose machine may generate a CT dose 10 times the radiationdose from a 15 milicurie FDG injection. The dedicated machine entirelydoes away with the CT dose and drops the required FDG dose by factor offive to about 3 mCi. In exemplary embodiments, such dedicated machinesand the like can be used.

In exemplary embodiments, areas of increased or reduced activity in anorgan can indicate a disease, an injury, a response to an injury, orfunctional changes in areas that have been disconnected from theremainder of the brain or spinal cord because of injury to connectivestructures. Non-limiting examples of such diseases or injuries include atumor, stroke, infection, demyelinating disease, degenerative disease,dementia, ischemia, traumatic injury, shock wave injury, or primary ormetastatic cancer, to name a few. For example, if the organ is thebrain, areas of reduced activity can represent diffuse axonal injury,and/or represent areas of the brain disconnected from their source ofworkload. Functional connectivity MRI can be used to show which parts ofthe brain are communicating.

In exemplary embodiments, areas of disease or injury can be furtheranalyzed by determining a ratio of a number of voxels showing increasedactivity to a number of voxels showing decreased activity within thearea of disease or injury. Further analysis can include determining aratio of a number of voxels showing increased activity to a number ofvoxels showing decreased activity within the entirety of a diseased areaand/or at a border region between an area of disease or injury andnormal tissue.

In exemplary embodiments, an image of the organ can be obtained andanalyzed at a plurality of time points. Images obtained at differenttime points can be used, for example, to evaluate effectiveness of acourse of treatment of a subject or to evaluate progression of disease.

For example, an image of the brain can be obtained and analyzed at aplurality of time points during neurological surgery or duringneurological intensive care. Frequent serial brain PET studies can beused to guide neurological surgery and neurological intensive care ofbrain injured patients. In exemplary embodiments, periodic, ornon-periodic repeated assessments may provide a tool for demonstratingresponse to therapy in a timely manner. By way of non-limiting example,studies may be repeated, e.g., a minimal interval of about three hoursto a more common interval of daily, weekly, monthly, to name a few, todocument brain glucose metabolism, brain oxygen metabolism, brain bloodflow, and other vital parameters, to name a few. Some neurologicalsurgery procedures have operating room durations in excess of 10 hours.Neurological intensive care can last for months.

As another example, an image of the heart can be obtained and analyzedat a plurality of time points during cardiac surgery, during cardiacinterventional procedures, and/or during cardiac intensive care. Inexemplary embodiments, frequent serial heart PET studies can be used toguide cardiac surgery and cardiac interventional intensive care of heartinjured patients. Periodic and/or non-periodic repeated assessments mayprovide a tool for demonstrating response to therapy in a timely manner.Studies may be repeated, e.g., a minimal interval of about 5 minutes toa more common interval of daily, weekly, monthly, to name a few, todocument cardiac nutritional blood flow using rubidium 82, cardiac FDGmetabolism using fluorine 18; cardiac oxygen metabolism using oxygen 15,and other vital parameters, to name a few.

Voxels within an area of disease or injury in the organ can be analyzedat a plurality of time points, and a ratio of a number of voxels withinthe area showing increased activity over time to a number of voxelswithin the area showing decreased activity over time can be used as ameasure of whether the disease or injury is improving or not improving.For example, if the disease is cancer, a decrease in the ratio of thenumber of voxels within the area of disease showing increased activityover time to the number of voxels within the area of disease showingdecreased activity over time is indicative of a favorable outcome. Asanother example, if the disease is reduced blood flow to the area, anincrease in the ratio of the number of voxels within the area showingincreased activity over time to the number of voxels within the areashowing decreased activity over time is indicative of a favorableoutcome.

In exemplary embodiments, the subject can be any living organism,including any type of animals, such as humans.

The methods disclosed herein can comprise imaging the subject to obtainan image of the organ.

In exemplary embodiments, a system for assessing the activity of anorgan in a subject may comprise:

a) an imaging system comprising:

i) an imaging device for generating a quantitative three-dimensionalimage of the organ that is represented as voxels, wherein each voxelcontains information about the activity of a portion of the organ; and

ii) a computing device operatively connected to the imaging device andto a first display device; and

b) one or more computers operatively connected to the imaging system,comprising one or more processors, a memory unit, and acomputer-readable storage medium including computer-readable code thatis read by the one or more processors to perform a method comprising thesteps of:

i) receiving by the one or more computers the generatedthree-dimensional organ image;

ii) calculating by the one or more computers a mean of the activityrepresented by the voxels, wherein voxels representing values at upperand lower extremes are excluded from calculation of the mean;

iii) calculating by the one or more computers a standard deviation ofthe mean obtained in step ii), wherein voxels representing activityabove a certain standard deviation of the mean indicate areas of theorgan having increased activity and wherein voxels representing activitybelow a certain standard deviation of the mean indicate areas of theorgan having reduced activity; and

iv) generating by the one or more computers a representation of theorgan showing areas of the organ having increased activity and/orreduced activity.

In exemplary embodiments, the method performed by the one or moreprocessors can comprise displaying by the one or more computers thegenerated representation of the organ on a second display deviceoperatively connected to the one or more computers. The method performedby the one or more processors can also comprise transmitting from theone or more computers the generated representation of the organ to theimaging system so as to be displayed on the first display device.

In exemplary embodiments, the image of the organ can obtained using,e.g., positron emission tomography (PET), functional magnetic resonanceimaging (fMRI), any type or sequence of magnetic resonance imagingincluding diffusion tensor imaging (MRI); magnetic source imaging,optical imaging, computed tomography (CT) X-ray scan, or combinationsthereof, to name a few. In some exemplary embodiments, the image of theorgan may be obtained using positron emission tomography (PET), alone,or in combination with CT or MRI.

In exemplary embodiments, a system for assessing the activity of anorgan in a subject comprising one or more computing devices may compriseone or more processors, a memory unit, and a computer-readable storagemedium including computer-readable code that is read by the one or moreprocessors to perform a method comprising the steps of:

i) obtaining by the one or more computing devices a quantitativethree-dimensional image of the organ that is represented as voxels,wherein each voxel contains information about the activity of a portionof the organ generated by an imaging device;

ii) transmitting the generated three-dimensional organ image to one ormore analysis computing devices;

iii) obtaining a representation of the organ from the one or moreanalysis computing devices, wherein the representation shows areas ofthe organ having increased activity and/or reduced activity; and

iv) displaying the obtained representation on the display device.

In exemplary embodiments, the representation of the organ can begenerated using the transmitted three-dimensional organ image at the oneor more analysis computers by a method comprising, e.g., the steps of:

i) calculating a mean of the activity represented by the voxels of thethree-dimensional organ image, wherein voxels representing values atupper and lower extremes are excluded from calculation of the mean; and

ii) calculating a standard deviation of the mean obtained in step i),wherein voxels representing activity above a certain standard deviationof the mean indicate areas of the organ having increased activity andwherein voxels representing activity below a certain standard deviationof the mean indicate areas of the organ having reduced activity.

In exemplary embodiments, a voxel analysis of the patient's own organcan be used to establish mean voxel values. Median and mode voxel valuescan also be determined. The fundamental principles of voxel-basedmorphometric (VBM) methods are well known.

In exemplary embodiments, a histogram may be provided, ranging from −4standard deviations to +4 standard deviations, for example, in 0.1standard deviation steps illustrating the distribution of voxels withinthe boundaries of the organ being examined. This histogram display ofvoxels can be used to select those voxels which will be statisticallyanalyzed and graphically displayed. In a normal organ one expects aGaussian distribution of voxels.

In exemplary embodiments, voxels can be analyzed using, for example,commercially available software such as provided by MIM Software Inc.(Cleveland, Ohio).

In exemplary embodiments, volumetric three-dimensional outlines ofclusters can be viewed in a cinematic mode, for example, proceeding from−4 standard deviations toward −1 standard deviation thereby showingareas of each degree of damage. Similarly a cinematic review of +3standard deviation volumetric three-dimensional outlines allowsdemonstration of compensatory increase in neuronal function of undamagedstructures and other recruited pathways. Such analysis can furtherverify the reality of damaged tissue by demonstrating the reality ofcompensatory mechanisms.

Where clusters of inactivity or compensatory activity are found, inexemplary embodiments, different indicia such as color overlays, textlabels, boundary outlines or the like may be applied to the visualdisplay output. The display output can be a computer monitor but mayalso be high resolution printers as well, or other display devices.Three-dimensional volumetric displays of medical data are becomingincreasingly available.

According to an exemplary embodiment, the invention may include theability to generate a short, cycling presentation of the identifiedvoxels (inactive and/or compensatory) at a plurality of standarddeviations. This cycling presentation or animation may be presented inthree-dimensional contours of the organ. Three-dimensional contours ofdetails of degree of metabolism within areas of damage can besimultaneously displayed.

In exemplary embodiments, the number of voxels within thethree-dimensional boundaries defined by standard deviations, such as,for example, 3, 2.5, 2.0, 1.5, and 1.0 standard deviations above orbelow the mean of non-involved tissue within that patients organ can bemapped over time to provide a very sensitive analysis of response totherapy versus progression of disease.

In an exemplary embodiment, the brain quantitative analysis program mayautomatically cycle from the lowest transaxial slice to the highesttransaxial slice. In some exemplary embodiments, the thickness of theslice can be adjusted from 4 mm to 20 mm.

Exemplary embodiments of the present disclosure may be applicable to alarge range of noninvasive imaging modalities that can be used toaddress and quantitate changes in tissue physiology repair and diseaseprocesses over time.

In exemplary embodiments, clusters of voxels may be defined by deviantsfrom the mean and can clearly show both the epicenter, the umbra and thepenumbra of any imaginable physiological deviance within any organ, andmay be measured by any modality that is voxel-based. For example,imaging MRI, functional MRI, diffusion tensor MRI, and otherexperimental MRI sequences may be candidates for such analysis. Inexemplary embodiments, such modalities may include positron emissiontomography, magnetic resonance imaging, single photon emission computedtomography, CT, volumetric ultrasound, optical tissue imaging, and allother means of noninvasive volumetric imaging of living tissues.

In exemplary embodiments, symmetrical organs such as brain and kidneys,comparison can be made with the corresponding area in the contralateralside, bearing in mind that within the brain, the contralateral structuremay be up-regulated to compensate for decreased function in the injuredstructure.

In exemplary embodiments, diffuse axonal injuries in the brain maygenerally appear as scattered small areas of decreased glucosemetabolism on the gyri of the cerebral cortex. These lesions may bealmost impossible to visually identify because of their location on avariable terrain. In some exemplary embodiments, voxel-based thresholdimaging may clearly identify small scattered lesions.

In exemplary embodiments, objective quantification of the number, size,severity, and location of, for example, areas of decreased glucosemetabolism within the brain may be possible without the need of acontrol group. Thus, possible artifacts generated by arbitrary braindeformation may be avoided. In some exemplary embodiments, serialquantification of number, size, severity and location of injured areasmay provide objective documentation of quantitative response to therapy.For example, therapies such as drug intervention and rehabilitationintervention can be compared with the spontaneous natural history of theuntreated pathological process.

Within the brain, amyloid protein is commonly deposited at areas ofinjury, potentially leading to progressively greater injury over timedue to amyloid toxicity. In exemplary embodiments, amyloid brain imagingmay be a natural adjunct to fluorine 18 deoxyglucose brain imaging intraumatic brain injury.

There may be multiple patterns of injury following trauma to the brainincluding coup-contrecoup contusion of brain surfaces, axonal damage bypropagation of shear forces resulting in Wallerian degeneration anddeath of widely distributed neurons whose axons assembled into a tractwithin the path of shear forces.

In exemplary embodiments, baseline measurements may be made onindividuals involved in contact sports who can be tracked season byseason. In exemplary embodiments, the present invention can be used toidentify the vulnerable post-concussion time during which repeatedtrauma can produce disproportionate severe damage.

Military personnel can be screened for susceptibility to additionalblast injury predeployment, potentially decreasing the total number ofindividuals whose cumulative brain damage renders them nonfunctional.Most individuals have a degree of cognitive reserve which masks thebehavioral and neurological signs and symptoms of lesser degrees ofbrain injury.

According to exemplary embodiments, in any area of diseased tissue,adjacent voxels may include volumes of cells with improving metabolismadjacent to volumes of cells with declining metabolism. In someexemplary embodiments, the ratio of voxels advancing to voxels decliningmay be a measure of whether the overall physiology is favoringregeneration or death. In some exemplary embodiments, whether theprocess is cancer where one wants the decline to be predominant or areasof blocked blood flow where one wants the advance to be predominant,progress of the local physiological condition can be objectivelymeasured in a timely fashion to allow therapeutic intervention with nearreal-time monitoring of the results. This may allow one to measure thestatus of the region, intervene therapeutically, and then remeasure.

In exemplary embodiments, each patient, and each area of brainhypometabolism may require frequent monitoring to detect the localadvance decline ratio. For example, each patient and each area of brainhypometabolism may have differing dose response curves for anytherapeutic intervention.

In exemplary embodiments, the ratio of the number of voxelsimproving/number of voxels worsening in an anatomical area can provide aunique measure of overall disease progression and treatmenteffectiveness over time. In addition to the injured or diseased areaitself, the border between normal and abnormal tissue areas may beanother region of interest.

In exemplary embodiments, the number of voxels in each degree ofdeviance from the mean may be obtained, and serial images may bedisplayed, such as, for example, starting with those voxels that aremost negative (−4 standard deviations). Further, the obtained voxels maybe summed with all interval voxels to a selected endpoint, such as, forexample, −1.65 standard deviations. This may produce a quantitativethree-dimensional volumetric map of the range of disease. This map maybe electronically saved on any suitable computer-readable storage deviceand subsequently used to quantitatively compare with a second volumetricmap obtained after therapy in accordance with the expected time courseof disease resolution. For example, the second map may be obtained oneto three months after therapy relating to chronic conditions. In othersituations, the second map may be obtained one to three days aftertherapy relating to acute conditions.

In exemplary embodiments, the quantitative disease assessment takingplace at regular intervals may serve as an objective measurement of theefficacy of any drug or interventional therapy. For example, in alaboratory or a clinical research setting more frequent observations candocument the physiology of the repair sequence. Thus surrogate markersfor pharmacological intervention trials may be validated. These can beof immense help in drug discovery. These can also be of immense help indetermining whether an individual patient is benefiting from theintervention. Non-responders can be spared potential toxicity that isnot offset by benefit.

In some exemplary embodiments, a histogram display of all of the voxelswithin the defined boundaries of a disease process within a specificanatomical area may be provided. For example, an area of traumatic braininjury in the right frontal lobe may contain 500,000 voxels. 100,000 ofthese voxels may be located within plus and minus 1 millimeter of thetransition zone from affected tissue to normal tissue, the apparentvisual boundary of the disease process. The 100,000 voxels in thetransition zone will be expected to display a wide range of metabolicuptake values. The voxels which are more centrally located will also beexpected to exhibit a wide range of metabolic uptake values. All of thevoxels within the visual boundary of the disease process are likely tochange metabolic uptake over time as the cells improve or die.

In an exemplary embodiment, a software product may be used for detectingdiffuse axonal injuries in a brain. The software product may be anysuitable computer-readable storage media that contains instructions,that when executed, cause one or more computers to perform the steps:accessing a digital brain scan of a subject's entire brain;quantitatively identifying voxels having inactivity of, e.g., −1.65standard deviations or less from that of the entire brain, or activityof, e.g. +1.65 standard deviations or more; establishing a thresholdvalue for localizing one or more clusters of said identified voxels;applying a clustering algorithm to localize said one or more clusters;generating a revised digital brain scan image with visually perceptibleindicia associated with said one or more clusters localized; anddisplaying said revised digital brain scan image on an output device.

FIG. 1 shows, according to an exemplary embodiment, a method fordetecting diffuse axonal injuries. At step 105, a volumetric digitalbrain scan image of a subject's entire brain may be obtained oraccessed. At step 110, voxels may be quantitatively identified whichare, e.g., −1.5 standard deviations or less from that of the entirebrain which may indicate inactivity and/or are, e.g., +1.5 standarddeviations or more from the entire brain which may indicate compensatoryactivity. At step 115, one or more threshold values may be establishedfor localizing one or more clusters of said identified voxels. At step120, a clustering algorithm may be applied to localize said one or moreclusters using the one or more threshold values. For example, theclustering algorithm may be applied to the identified voxels above orbelow the 1.5 standard deviations from the brain. At step 125, one ormore indicias may be generated with respect to the one or more sets ofidentified clusters. Using the generated indicias, at step 130, arevised digital brain scan image with visually perceptible indiciaassociated may be generated. At step 135, a revised digital brain scanimage may be displayed on an output device. At step 140, based on thegenerated image, alternative pathways to and from the areas ofidentified areas of compensatory activity may be stimulated.

In some exemplary embodiments, the method as illustrated in FIG. 1 mayfurther comprise the steps of: accessing a digital brain scan image of asubject's entire brain; quantitatively identifying voxels havinginactivity of at a plurality of standard deviations less than, e.g.,−1.0; establishing a threshold value for localizing one or more clustersof said identified voxels; applying a clustering algorithm to localizesaid one or more clusters; sequentially generating a plurality ofrevised digital brain scan images with visually perceptible indiciaassociated with said one or more clusters localized at each standarddeviation value; and displaying said revised digital brain scan image onan output device.

According to an exemplary embodiment, diffuse axonal injuries may bedetected in a brain by implementing a method comprising the steps of:accessing a digital brain scan image of a subject's entire brain;quantitatively identifying voxels having compensatory activity of at aplurality of standard deviations greater than, e.g., 1.0; establishing athreshold value for localizing one or more clusters of said identifiedvoxels; applying a clustering algorithm to localize said one or moreclusters; sequentially generating a plurality of revised digital brainscan images with visually perceptible indicia associated with said oneor more clusters localized at each standard deviation value; anddisplaying said revised digital brain scan images on an output device.In some exemplary embodiments, the revised digital brain scan images maybe presented in three-dimensional contours.

According to another exemplary embodiment, FIG. 2 shows an imagingsystem, generally designated by number 5. The imaging system 5 mayinclude one or more imaging devices designated by number 10, that may beoperatively connected to one or more computing devices generallydesignated by number 20. The imaging device 10 may generate anquantitative three-dimensional image of an organ, such as, for example,a brain, heart, lung, kidney, liver, pancreas, bladder, salivary glands,esophagus, stomach, gallbladder, intestines, colon, rectum, thyroid,parathyroid, adrenal gland, ureter, bladder, urethra, tonsils, adenoids,thymus, spleen, ovary, fallopian tube, uterus, vagina, mammary gland,testes, vas deferens, seminal vesicle, prostate, penis, pharynx, larynx,trachea, bronchi and lung, to name a few. In exemplary embodiments, theimage of the organ may be generated using positron emission tomography(PET), computed tomography (CT) X-ray scan, functional magneticresonance imaging (fMRI), magnetic source imaging or optical imaging, orcombinations thereof. For example, the three-dimensional imaging maybeobtained using a PET scan in connection with a CT X-ray scan.

In exemplary embodiments, the imaging system 10, and by extension, anyone of its components, may be operatively connected to one or morecomputer networks 50, such as, for example, the Internet, or any othersuitable network, via, by way of example, a set of routers and/ornetworking switches. The imaging system 10 may be connected to animaging analysis system 30 or any one of its components. For example,the imaging analysis system 30 may include one or more analysiscomputers, designated by number 40. The analysis computers 40 mayinclude one or more processors, computer readable storage media, andmemory units. The one or more processors may read and execute softwareembodied as instructions stored on the computer readable storage media,according to exemplary embodiments herein.

In exemplary embodiments, the analysis system 30 may be used to assessthe activity of organ. Referring to FIG. 2, at step 205, the analysiscomputers 40 may obtain a image scan of an organ. The organ may be froman animal, including a human. The image scan data generated by theimaging device 10 may be sent directly or indirectly to the analysissystem 30.

The obtained image scan may be a quantitative three-dimensional image ofthe organ. This image or image scan may include voxels or voxel data,wherein each voxel contains information about the activity of a portionof the imaged organ. In one exemplary embodiment, the imaging device 10may generate a PET scan of the organ in a Digital Imaging andCommunications in Medicine (DICOM) format. In this regard, the image orscan data may contain at least four elements as follows: an xcoordinate, a y coordinate, a z coordinate, and a value measured at thex, y, and z coordinates. Since DICOM is a standard covering both dataformats and protocols for communications, the image scan/data may beobtained several ways. See DICOM at: http://en.wikipedia.org/wiki/DICOM.

At step 210, the obtained image scan may be used by the analysiscomputers 40 to calculate activity using the voxels. For example, themean of the activity represented by the voxels may be calculated. Insome exemplary embodiments, voxels representing extreme upper and lowervalues may be excluded. Voxels representing values at the upper and/orlower 1%, 5%, 10%, or any other appropriate voxels representing valuesin an extreme range may be excluded.

At step 215, the analysis computers 40 may further, based on thecalculated mean, calculate one or more voxel threshold values. In anexemplary embodiment, the analysis computers 40 may calculate a standarddeviation using the calculated mean. For example, the standard deviationmay be calculated in 0.1 standard deviation (SD) units between 4.0 SDunits below the mean to 4.0 SD units above the mean. In some exemplaryembodiments, the standard deviation may be calculated in 0.01 standarddeviation (SD) units. In some embodiments, the standard deviation may becalculated in units between 3.0 SD units below the mean to 3.0 SD unitsabove the mean.

At step 220, the analysis computers may determine voxels are outside orbeyond the calculated threshold values. The analysis computers 40 maydetermine voxels which are a specified standard deviation above or belowthe mean, as such voxels may respectively indicate areas of the organwith increased or decreased activity. For example, voxels representingactivity 1.65 SD units above or below the mean may indicate,respectively, increased or decreased activity. In some exemplaryembodiments, other standard deviation unit values may be used toindicate activity/inactivity. For example, voxels representing activityanywhere from 1.00-4.00 SD units above or below the mean may indicateincreased or decreased activity.

At step, 225, the calculated data regarding the voxels may be stored,such as in databases 35, for future use. At step 230, a representationof the organ, based on the calculations performed by the analysiscomputers 40, may be outputted to an output device to show the areas ofthe organ with increased and/or decreased activity. For example, theanalysis computers 40 may be connected to a display device to displaythe representation of the organ. In some exemplary embodiments, thedisplayed representation may be a histogram.

In some exemplary embodiments, software such as the MIMneuro may be usedat least by the analysis computers 40 to perform one or more of thecalculations and generate a representative output based on suchcalculations, such as for example a histogram.

In some exemplary embodiments, the representation of the outputrepresentation of the organ showing increased/decreased activity may besent from the analysis computers 40 to the imaging system 10. Forexample, the output representation may be displayed a on a displayoperatively connected to the computer 20. The imaging device 10 and/orcomputer may be located any suitable locations, such as, for example, adoctor's office, a hospital, a clinic, to name a few.

The output representation and associated calculations related to theorgan may be used by a physician. In an exemplary embodiment, aphysician may observe a representation, such as histogram of the organscan. For example, the physician may select a range of histogram barsrepresenting voxel values that are a certain amount of standarddeviations away from the mean for the entire organ scan, such as forexample, 1.5 SD units, 1.65 units, to an name a few. In this regard,such a selection may be symmetrical about the mean. For instance, if alarge count of voxels (i.e. a spike) occurs at −1.3 standard deviations,then something less than 1.3 standard deviations will be selected as the“normal range” both above the mean and below the mean, and equidistantfrom the mean. Further, the physician may perform a visual verificationof the normal area. Further, the analysis computers 40 or computer 20may be used to display a visual map of the scan data that highlights the“normal area” as a result the physician's selection. If the selectionverifies, then the mean, median and mode may be calculated and storedfor future comparisons.

In exemplary embodiments, areas of increased or reduced activity in theorgan indicate a disease or an injury, such as, for example, a tumor,stroke, infection, demyelinating disease, degenerative disease,dementia, ischemia, traumatic injury, or primary or metastatic cancer,to name a few. For example, with respect to the brain, areas of reducedactivity in the organ may represent diffuse axonal injury.

Further processing regarding the voxels may include rescaling the voxelsand calculating an advance/decline ratio. The voxels may be rescaled soas to eliminate any biases, with any scaled data and/or scaling factorsmay be stored for future reference. The advanced/decline ratio may alsobe stored for future reference. In addition, depending on the type oforgan imaged, the voxels from one side of the imaged organ may becompared with the corresponding voxels on the opposite side of the sameorgan. Similarly, voxels from one organ on side of the body may becompared with corresponding voxels on the corresponding organ on theopposite side of the body.

Analyses preformed using the voxels may include determining a ratio of anumber of voxels showing increased activity to a number of voxelsshowing decreased activity at a border region between an area of diseaseor injury and normal tissue.

The process of accessing organ activity as illustrated in FIG. 2 may berepeated over a period of time at certain intervals so as to determineany changes in activity. In this regard, an image of the organ mayobtained and analyzed at a plurality of time points. The images obtainedat different time points may be used to evaluate effectiveness of acourse of treatment of a subject or to evaluate progression of disease.The voxels within an area of disease or injury in the organ may beanalyzed at a plurality of time points and a ratio of a number of voxelswithin the area showing increased activity over time to a number ofvoxels within the area showing decreased activity over time may be ameasure of whether the disease or injury is improving or not improving.

In the case of a human brain being imaged/scanned, psychometric testsmay be used in addition or in conjunction with to assess and/evaluatethe brain and its activity.

In situations where a brain is being analyzed or accessed, a pluralityof psychometric tests may also be administered with respect to thepatient over the same period of time. In any event, after the process isrepeated various things may be tracked, such as for example, theabsolute number of voxels, the advanced/decline ratio, and thepercentage of activity change in certain areas, to name a few. FIGS.4A-4B, shows results of various psychometric tests that may administeredover a 1 year time period.

It will be seen that the advantages set forth above, and those madeapparent from the foregoing description, are efficiently attained andsince certain changes may be made in the above construction withoutdeparting from the scope of the invention, it is intended that allmatters contained in the foregoing description or shown in theaccompanying drawings shall be interpreted as illustrative and not in alimiting sense. This invention will be better understood from theExperimental Details, which follow. However, one skilled in the art willreadily appreciate that the specific methods and results discussed aremerely illustrative of the invention as described more fully in theclaims that follow thereafter.

EXPERIMENTAL DETAILS Case Study #1 Quantitative Evaluation PostHyperbaric Oxygen Therapy

History:

RM, a 46 year old male suffered traumatic brain injury when he fell onhis head from a loft, a distance of 8 feet in February 1997. The patientwas severely incapacitated, declared totally and permanently disabled bySocial Security and was evaluated at Mayo Clinic Jacksonville. Withremarkable persistence in a self-directed rehabilitation program, he wasable to resume gainful employment after several years. Subsequently, thepatient reported hitting his head from a major bicycle accident andhitting his head when he walked into an obstruction at a warehouse.Patient self-referred in May 2011 with complaints of anxiety,depression, intermittent dissociation, decreased ability to concentrate,and memory loss. At the time of referral, the patient had beenself-medicating with alcohol and had stopped self-directedrehabilitation.

Care Plan:

The patient was advised to abstain from self-medicating with alcohol. Rx50 mg Trazadone at night. Self-directed 45 hours of 1.3 atmosphericpressure 90% oxygen.

PET Studies:

Upon referral (May 3, 2011) patient received a Quantitative PET brainstudy and underwent multiple cognitive and self-reporting psychometrictesting during the following 12 month period. On Aug. 18, 2011 (75 dayslater) the patient received a second Quantitative PET brain study andcontinued cognitive and psychometric testing. The PET studies wereanalyzed using a custom neurological software package.

Referring to FIGS. 5A and 5B, Comparative Quantitative Imaging showedsignificant improvement from May 2011 to February 2012 consistent withimproved Cognitive scores (Table 1). Significant improvement is notedespecially in frontal lobes. Referring to FIG. 5A, the patient's brainis imaged showing areas 501, 502, 503, 504, and 505 with decreasedactivity. FIG. 5B shows the imaged brain in February 2012, withimprovement in those same areas.

RM has had about seventy 1.3 atmosphere hyperbaric treatments sinceNovember, 2011. Patient reports mediation 3 to 5 times a week, nodrinking, and consistent vitamin B complex use since Nov. 26, 2011. Hisfamily and economic stress level are twice as high as compared to a yearago. RM has shown remarkable improvement in frontal lobe PET scanhypometabolism, remarkable improvement in Processing Speed, andsignificant improvement in Neurocognitive Index.

TABLE 1 A. Cognitive changes over time for Case Study #1 03- 12- 17- 21-10- 15- 17- 25- 30- 09- 24- May Jul Jul Jul Aug Aug Aug Aug Aug Nov JanNC 63 68 66 73 81 87 82 93 90 77 70 index Comp 21 40 63 30 45 75 50 9034 61 55 M Verbal 12 30 58 63 12 55 63 79 30 37 63 M Visual 45 53 66 1381 81 37 90 45 75 45 M Psych 86 84 34 96 96 96 98 96 99 94 90 motorspeed RT 42 45 70 58 93 95 86 86 93 66 32 CA 82 82 63 63 58 58 58 70 7777 82 CF 70 81 87 90 86 90 96 96 97 78 82 Proc 5 5 13 40 18 34 27 75 5318 4 speed Exec 68 84 86 95 88 93 98 96 97 81 81 func Total 494 572 606621 658 764 695 871 715 664 604 B. Cognitive changes over time for CaseStudy #1 (Continuation of Table 1A) 31- 04- 06- 04- 11- 21- 26- 18- 23-02- Jan Feb Feb Mar Mar Mar Jan Apr Apr May NC 63 82 82 90 90 84 91 9393 95 1713 index Comp 12 70 40 79 70 61 82 70 61 61 1170 M Verbal 16 7930 90 90 73 63 63 73 63 1142 M Visual 18 53 53 53 37 45 86 68 45 53 1142M Psych 95 99 99 99 99 99 99 99 99 99 1955 motor speed RT 58 70 79 73 8168 82 86 75 75 1513 CA 77 70 82 82 82 70 77 70 82 82 1544 CF 66 79 87 9493 81 95 96 96 98 1838 Proc 25 53 77 53 63 92 75 97 96 99 1022 speedExec 66 79 86 95 93 79 96 96 96 98 1851 func Total 496 734 715 808 798752 846 838 816 823 NC index—Neuro-cognitive index, Comp M—Compositememory, Verbal M—Verbal memory, Visual M—Visual Memory, Psych motorspeed—Psycho-motor speed, RT—Reaction time, CA—Complex attention,C—Cognitive flexibility, Proc speed—Processing speed, Execfunc—Executive function

Case Study #2 NFL PLAYER

Clinical Diagnosis:

traumatic brain injury with persistent symptoms: severe headaches,memory loss requiring constant notations in a diary, difficulties withanger and rage, difficulty sleeping, sleepwalking, talking in his sleep,“terrible” “horrible” short-term memory, and perceptions of spaceclosing in on him, especially in crowds.

He experiences significant visual impairment, as well as severedizziness if he bends over after exercise. He finds a 45 minute trip onthe interstate very difficult. He is chronically frustrated and upset.He is in marital counseling. He has just experienced the thirdanniversary of his second marriage. He has children by his firstmarriage ages 24 and 18. He divorced in 2008. He is currentlyunemployed; applying for social security disability.

Summary of Brain Surface Visual Findings:

Cortical confluent hypometabolic areas are seen at the base of the braincentering on the brainstem, pons, cerebellar vermis and cerebellarpeduncles. The inferior aspects of cortical and subcortical regions ofboth temporal lobes are hypometabolic; the medial aspects of bothcerebellar hemispheres are involved; there is also significant spottycortical and subcortical hypometabolism of the inferior aspects of thefrontal lobes. Midline images of the brain demonstrate severe extensivehypometabolism of the basal ganglia and midbrain.

Right Frontal Lobe:

there is a severely hypometabolic right frontal lobe area measuring 4.9cm in height by 1.4 cm in width by 1.25 cm in anterior-posteriordimension involving most of the right superior frontal gyrus. There is alarge area of hypometabolism involving the right inferior frontal gyruspars triangularis measuring 2.5 cm in height by 1.4 cm in width by 1.9cm in anterior-posterior dimension. The right frontal gyrus ishypometabolic; right superior frontal gyrusis hypometabolic; rightmiddle frontal gyrus is hypometabolic; right orbitofrontal regionincluding the medial orbital gyrus is hypometabolic. Right supplementarymotor area is extensively hypometabolic. Right precentral gyrus containsa hypometabolic area measuring 2 cm in height by 1.8 cm in width. Theright superiormedial frontal gyrus is severely hypometabolic measuring2.8 cm in length by 1.5 cm in width.

Left Frontal Lobe:

There is a mirror image hypometabolic area measuring 2.3 cm in height by0.7 cm in width involving much of the left superior frontal gyrus.Hypometabolism is extensive in the left orbitofrontal region includingthe medial orbital gyrus. The left anteriororbital gyrus ishypometabolic. The right inferior medial frontal gyrus is hypometabolic;left superior frontal gyrus measuring 0.7 cm diameter is severelyhypometabolic, left middle frontal gyrus is hypometabolic. Leftsupplementary motor area is extensively hypometabolic. Left middlefrontal gyrus is hypometabolic. Left superior frontal gyrus ishypometabolic; left precentral gyrus is hypometabolic; left superiorfrontal gyrus is hypometabolic. The left superior medial frontal gyrusis severely hypometabolic measuring 2 cm in anterior-posterior dimensionand about 1.5 cm in width.

Insula:

There is focal hypometabolism within the right insula.

Right Temporal Lobe:

Hypometabolism of the inferior aspects of the right temporal lobeextending into the medial area. The right fusiform gyrus is extensivelyhypometabolic; right hippocampus is extensively hypometabolic measuring2.9 cm in height by 1.3 cm in width by 4.4 cm in obliqueanterior-posterior length. Right temporal pole is hypometabolic.

Left Temporal Lobe:

Hypometabolism of the inferior aspects of the left temporal lobeextending into the medial area as is the left fusiform gyrus. The lefttemporal pole is hypometabolic; the left fusiform gyrus is involved. Theleft hippocampus is significantly hypometabolic.

Right Parietal Lobe:

The right rolandic operculum is hypometabolic; The right super marginalgyrus is hypometabolic. The right precentral gyrus is hypometabolic. Theright posterior cingulate gyrus is hypometabolic. The right superiorparietal lobule is extensively hypometabolic. The right precentral gyrusis hypometabolic. The right superior parietal lobule is extensively andseverely hypometabolic. The right angular gyrus is hypometabolic as isthe right supra-marginal gyrus.

Left Parietal lobe:

The left rolandic operculum is hypometabolic. The left super marginalgyrus is hypometabolic; the left precentral gyrus is hypometabolic; theleft postcentral gyrus is hypometabolic; left superiorparietal lobule ishypometabolic; the left pre-post central gyrus is hypometabolic; theleft superior parietal lobule is very extensively and severelyhypometabolic. Left supra marginal gyrus is hypometabolic. Left angulargyrus is hypometabolic.

Basal Ganglia:

The putamen is hypometabolic bilaterally. The globis pallidusbilaterally is extensively hypometabolic.

Thalamus:

The right thalamus is severely hypometabolic measuring about 3 cm inheight by 2.1 cm in anterior-posterior dimension. Left thalamus isseverely hypometabolic measuring 4.2 cm in height by 2.2 cm in width.

Right Occipital Lobe:

The right superior occipital gyrus shows extensive hypometabolism. Thereis definite involvement of the right primary visual cortex. The rightlingual gyrus inferior to the right primary visual cortex is alsoseverely hypometabolic.

Left Occipital Lobe:

There is definite involvement of the left primary visual cortexmeasuring 2.3 cm in height by 1.3 cm in width, by 2.6 cm inanterior-posterior dimension. There is very extensive involvement of theleft primary visual cortex. The left superior occipital gyrus hasextensive hypometabolism. Adjacent structures in the left occipital lobeare also hypometabolic. The left lingual gyrus is hypometabolic and theright superior occipital gyrus is hypometabolic; the right fusiformgyrus is hypometabolic. The left fusiform gyrus and left inferioroccipital gyrus are focally hypometabolic

Cerebellum:

There is extensive hypometabolism involving the right inferior andsuperior cerebellar peduncles. There is moderately extensivehypometabolism of the left inferior and superior cerebellar peduncles.The midline cerebellar vermis is extensively hypometabolic measuring 2.4cm in width by 1.14 cm anterior-posterior.

Quantitative Findings:

Areas of the brain where the hypometabolism is so severe and extensivethat the average metabolic rate of the entire structure is statisticallydepressed.

TABLE 2 Areas of extensive hypometabolism in Case Study #2. StructureMidline Left Right base of po −2.4 SD globis pallidus −2.2 SD −2.2 SDsuperior cerebellar −0.9 SD −2.1 SD peduncle middle cerebellar −1.0 SD−1.5 SD peduncle inferior cerebellar −0.7 SD −1.8 SD peduncle brainstem−1.4 SD thalamus −1.3 SD −1.4 SD primary visual cortex −1.3 SD −1.2 SDlingual gyrus −1.0 SD −1.2 SD amygdala −1.2 SD −0.6 SD Example: −2 SDmeans 97.5% of people function better.

TABLE 3 Percentages of regions of brain showing hypometabolism. Max MinVolume % Contour (z-score) (z-score) (ml) Volume WHOLE BRAIN 4.21 −4.912417.8 WHOLE BRAIN HYPO −1.65 −4.91 123.9 5.1% Frontal Lobe 4.21 −4.91576.9 Frontal Lobe Hypo −1.65 −4.91 32.1 5.6% Occipital Lobe 3.66 −3.94225.7 Occipital Lobe Hypo −1.65 −3.94 15.3 6.8% Parietal Lobe 3.71 −4.77341.8 Parietal Lobe Hypo −1.65 −4.77 23.7 6.9% Temporal Lobe 3.66 3.94307.3 Temporal Lobe Hypo −1.65 −3.94 9.8 3.2% Hypo: hypometabolism.

Impressions:

This patient demonstrates extensive severe traumatic brain injury inboth the right and left sides of his brain. Very severe memoryimpairment is directly traceable to hypometabolism in both hippocampi,and bilaterally in the thalamus. Visual difficulties are directlytraceable to bilateral hypometabolism in the primary visual cortex.Difficulties with emotional self-regulation are directly correlated withhypometabolism in both amygdala, as well as extensive areas ofhypometabolism in the frontal cortex bilaterally.

REFERENCES

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1. A method for assessing the activity of an organ in a subject with theaid of a digital computer comprising: a) accessing by one or morecomputers a quantitative three-dimensional image of the organ that isrepresented as voxels, wherein each voxel contains information about theactivity of a portion of the organ; b) calculating by the one or morecomputers a mean of the activity represented by the voxels, whereinvoxels representing values at upper and lower extremes are excluded fromcalculation of the mean; c) calculating by the one or more computers astandard deviation of the mean obtained in step b), wherein voxelsrepresenting activity above a certain standard deviation of the meanindicate areas of the organ having increased activity and wherein voxelsrepresenting activity below a certain standard deviation of the meanindicate areas of the organ having reduced activity; and d) outputtingby the one or more computers to an output device a representation of theorgan showing areas of the organ having increased activity and/orreduced activity.
 2. The method of claim 1, comprising outputting by theone or more computers to the output device a representation of the organshowing areas of the organ having neither increased activity and/orreduced activity.
 3. The method of claim 1, wherein in step b) voxelsare excluded from the calculation of the mean if the voxels representvalues at the upper and lower 5% of the values.
 4. The method of claim1, wherein standard deviation (SD) is calculated in 0.1 SD units between3.0 SD units below the mean to 3.0 SD units above the mean.
 5. Themethod of claim 1, wherein voxels representing activity above 1.5 SDunits above the mean indicate areas of the organ having increasedactivity and wherein voxels representing activity below 1.5 SD unitsbelow the mean indicate areas of the organ having reduced activity. 6.The method of claim 1, wherein the organ is at least one selected fromthe group consisting of brain, heart, lung, kidney, liver, pancreas,bladder, salivary glands, esophagus, stomach, gallbladder, intestines,colon, rectum, thyroid, parathyroid, adrenal gland, ureter, bladder,urethra, tonsils, adenoids, thymus, spleen, ovary, fallopian tube,uterus, vagina, mammary gland, testes, vas deferens, seminal vesicle,prostate, penis, pharynx, larynx, trachea, bronchi and lung.
 7. Themethod of claim 1, wherein voxels from the one side of an organ arecompared with corresponding voxels from an opposite side of the sameorgan.
 8. The method of claim 1, wherein voxels from an organ on oneside of the body are compared with corresponding voxels from thecorresponding organ on the opposite side of the body.
 9. The method ofclaim 1, wherein the image of the organ is obtained using positronemission tomography (PET), functional magnetic resonance imaging (fMRI),diffusion tensor magnetic resonance imaging, magnetic resonance imagingof any form, single photon emission computed tomography (SPECT) magneticsource imaging or optical imaging.
 10. The method of claim 1, whereinthree dimensional imaging of the organ is obtained using positronemission tomography (PET) in connection with a computed tomography (CT)X-ray scan.
 11. The method of claim 1, wherein three dimensional imagingof the organ is obtained using positron emission tomography (PET) inconnection with any magnetic resonance scan.
 12. The method of claim 1,wherein areas of increased or reduced activity in the organ indicate adisease, an injury, a response to an injury, or functional changes inareas that have been disconnected from the remainder of the brain orspinal cord because of injury to connective structures.
 13. The methodof claim 12, wherein the disease or injury is a tumor, stroke,infection, demyelinating disease, degenerative disease, dementia,ischemia, traumatic injury, shock wave injury, or primary or metastaticcancer.
 14. The method of claim 12, wherein the organ is the brain andareas of reduced activity in the organ represent diffuse axonal injury.15. The method of claim 1 comprising determining a ratio of a number ofvoxels showing increased activity to a number of voxels showingdecreased activity within an area of disease or injury.
 16. The methodof claim 1 comprising determining a ratio of a number of voxels showingincreased activity to a number of voxels showing decreased activity at aborder region between an area of disease or injury and normal tissue.17. The method of claim 1, wherein an image of the organ is obtained andanalyzed at a plurality of time points.
 18. The method of claim 17,wherein images at different time points are used to evaluateeffectiveness of a course of treatment of a subject or to evaluateprogression of disease.
 19. The method of claim 17, wherein an image ofthe brain is obtained and analyzed at a plurality of time points duringneurological surgery or during neurological intensive care.
 20. Themethod of claim 17, wherein an image of the heart is obtained andanalyzed at a plurality of time points during cardiac surgery, duringcardiac interventional procedures, or during cardiac intensive care. 21.The method of claim 17, wherein voxels within an area of disease orinjury in the organ are analyzed at a plurality of time points, and aratio of a number of voxels within the area showing increased activityover time to a number of voxels within the area showing decreasedactivity over time is a measure of whether the disease or injury isimproving or not improving.
 22. The method of claim 21, wherein thedisease is cancer and wherein a decrease in the ratio of the number ofvoxels within the area of disease showing increased activity over timeto the number of voxels within the area of disease showing decreasedactivity over time is indicative of a favorable outcome.
 23. The methodof claim 21, wherein the disease is reduced blood flow to the area andwherein an increase in the ratio of the number of voxels within the areashowing increased activity over time to the number of voxels within thearea showing decreased activity over time is indicative of a favorableoutcome.
 24. The method of claim 1, wherein the subject is an animal.25. The method of claim 24, wherein the subject is a human.
 26. Themethod of claim 1, which comprises imaging the subject to obtain animage of the organ.